fix(litellm_logging.py): log response_cost=0 for failed calls

Fixes BerriAI#4604

litellm/cost_calculator.py

@@ -737,8 +737,8 @@ def response_cost_calculator(
  )
  return None
  except Exception as e:
- verbose_logger.error(
- "litellm.cost_calculator.py::response_cost_calculator - Exception occurred - {}/n{}".format(
+ verbose_logger.warning(
+ "litellm.cost_calculator.py::response_cost_calculator - Returning None. Exception occurred - {}/n{}".format(
  str(e), traceback.format_exc()
  )
  )

litellm/litellm_core_utils/litellm_logging.py

@@ -1499,6 +1499,7 @@ def _failure_handler_helper_fn(
  self.model_call_details["traceback_exception"] = traceback_exception
  self.model_call_details["end_time"] = end_time
  self.model_call_details.setdefault("original_response", None)
+ self.model_call_details["response_cost"] = 0
  return start_time, end_time
 
  def failure_handler(

litellm/proxy/_new_secret_config.yaml

@@ -1,33 +1,4 @@
 model_list:
- - model_name: azure-ai-mistral
+ - model_name: ollama-mistral
  litellm_params:
- api_base: os.environ/AZURE_AI_MISTRAL_API_BASE
- api_key: os.environ/AZURE_AI_MISTRAL_API_KEY
- model: azure_ai/Mistral-large-nmefg
- input_cost_per_token: 0.00001
- output_cost_per_token: 0.000004
- - model_name: azure-ai-phi
- litellm_params:
- api_base: os.environ/AZURE_AI_PHI_API_BASE
- api_key: os.environ/AZURE_AI_PHI_API_KEY
- model: azure_ai/Phi-3-medium-128k-instruct-fpmvj
- - model_name: dbrx
- litellm_params:
- model: databricks/databricks-dbrx-instruct
- api_key: os.environ/DATABRICKS_API_KEY
- api_base: os.environ/DATABRICKS_API_BASE
- input_cost_per_token: 0.00000075
- output_cost_per_token: 0.00000225
-
-
-
-general_settings:
- master_key: sk-1234
- pass_through_endpoints:
- - path: "/v1/rerank"
- target: "https://api.cohere.com/v1/rerank"
- auth: true # 👈 Key change to use LiteLLM Auth / Keys
- headers:
- Authorization: "bearer os.environ/COHERE_API_KEY"
- content-type: application/json
- accept: application/json
+ model: ollama/mistral

litellm/tests/test_completion_cost.py

@@ -42,6 +42,14 @@ async def async_log_success_event(self, kwargs, response_obj, start_time, end_ti
 
  print(f"response_cost: {self.response_cost} ")
 
+ def log_failure_event(self, kwargs, response_obj, start_time, end_time):
+ print("Reaches log failure event!")
+ self.response_cost = kwargs["response_cost"]
+
+ async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time):
+ print("Reaches async log failure event!")
+ self.response_cost = kwargs["response_cost"]
+
 
 @pytest.mark.parametrize("sync_mode", [True, False])
 @pytest.mark.asyncio
@@ -74,6 +82,41 @@ async def test_custom_pricing(sync_mode):
  assert new_handler.response_cost == 0
 
 
+@pytest.mark.parametrize(
+ "sync_mode",
+ [True, False],
+)
+@pytest.mark.asyncio
+async def test_failure_completion_cost(sync_mode):
+ new_handler = CustomLoggingHandler()
+ litellm.callbacks = [new_handler]
+ if sync_mode:
+ try:
+ response = litellm.completion(
+ model="gpt-3.5-turbo",
+ messages=[{"role": "user", "content": "Hey!"}],
+ mock_response=Exception("this should trigger an error"),
+ )
+ except Exception:
+ pass
+ time.sleep(5)
+ else:
+ try:
+ response = await litellm.acompletion(
+ model="gpt-3.5-turbo",
+ messages=[{"role": "user", "content": "Hey!"}],
+ mock_response=Exception("this should trigger an error"),
+ )
+ except Exception:
+ pass
+ await asyncio.sleep(5)
+
+ print(f"new_handler.response_cost: {new_handler.response_cost}")
+ assert new_handler.response_cost is not None
+
+ assert new_handler.response_cost == 0
+
+
 def test_custom_pricing_as_completion_cost_param():
  from litellm import Choices, Message, ModelResponse
  from litellm.utils import Usage

litellm/utils.py

@@ -694,7 +694,7 @@ def wrapper(*args, **kwargs):
  kwargs["litellm_call_id"] = str(uuid.uuid4())
  try:
  model = args[0] if len(args) > 0 else kwargs["model"]
- except:
+ except Exception:
  model = None
  if (
  call_type != CallTypes.image_generation.value